The AI Engineer role today
This guide draws on 726 AI Engineer postings from 456 companies, published from March to September 2026.
AI Engineer is a core AI role: in 74% of postings, building or applying AI is the job itself.
Prompt Engineering appears in 42% of AI Engineer postings, and MLOps in 34%.
Automation exposure averages 22 out of 100 across these postings, which is low: AI mostly supports this work rather than taking it over.
Senior positions make up 42% of postings, entry-level 20%. The most common way of working is hybrid, in 51% of postings.
Common skill gaps
The AI skills our analysis of AI Engineer job descriptions most often flags as a gap, with the share of postings where each one comes up.
- Prompt Engineering22%
- AI Safety and Red Teaming17%
- AI Governance Frameworks16%
- MLOps14%
- AI Safety Red Teaming14%
- AI Governance11%
AI Engineer salary
Pay comes only from postings that quote it: 28 of the 726 AI Engineer postings. Each country uses the pay period its employers quote most.
Netherlands
based on 28 postings quoting pay per month€5,600
median per month
The middle half of advertised salaries, with the line at the median.
Essential AI Engineer skills
The skills employers ask for in AI Engineer job descriptions, from the most requested down.
Core skills
- Python
- Prompt Engineering
Often requested
- MLOps
- LLM Application Development
- RAG Pipelines
Also valued
- Machine Learning
- Vector Databases
- Generative AI
- Retrieval Augmented Generation
- Model Evaluation
AI skills to learn next
The AI skills employers most often want to add to this role, beyond the ones above.
- AI Security
- LLM Ops
- LLM Fine Tuning
How the AI Engineer role is evolving
The directions employers are taking this role as they adopt AI, with the skills and responsibilities each one adds.
Most common direction
Toward AI engineering
Typical focus
Agentic systems and LLM systems
Skills to add
- Multi Agent Orchestration
- Multi Agent Systems
New responsibilities
- Design and implement multi-agent systems for complex task automation
- Lead the design and implementation of multi-agent systems for complex enterprise workflows
- Establish best practices for prompt engineering and LLM evaluation
- Mentor junior engineers on AI best practices and emerging technologies
Other directions
Toward AI product
Typical focus
Product innovation and Product & platform
Skills to add
- AI Product Strategy
- Stakeholder Management
- AI Product Management
- Cross Functional Collaboration
- User Experience for AI
- AI Roadmapping
New responsibilities
- Translate business requirements into technical AI solutions
- Partner with product managers to define AI feature roadmaps and success metrics
- Collaborate with product managers to define AI feature roadmaps
Toward AI transformation
Typical focus
Enterprise transformation
Skills to add
- Change Management
- AI Strategy
- AI Change Management
- Stakeholder Communication
New responsibilities
- Develop AI adoption roadmaps and transformation strategies for enterprise clients
- Facilitate workshops to identify high-impact AI use cases
- Develop and deliver AI literacy workshops for non-technical stakeholders
- Develop and execute AI adoption roadmaps across business units
Toward data & machine learning
Typical focus
MLOps & data pipelines, Data & model operations and Data & ML platforms
Skills to add
- Model Monitoring
- Data Versioning
- Feature Store
- CI CD for ML
- Distributed Training
New responsibilities
- Implement monitoring and alerting for model performance and data drift
- Monitor model performance and data drift in production
- Build and maintain CI/CD pipelines for machine learning models
- Build and maintain feature stores for ML model training and inference
AI Engineer FAQ
Will AI replace AI Engineer jobs?
Automation exposure averages 22 out of 100 across these postings, which is low: AI mostly supports this work rather than taking it over. Employers are mostly reshaping the role toward AI engineering, adding skills such as Multi Agent Orchestration and LLM Ops.
What skills do AI Engineer roles require?
The skills employers ask for most are Python, Prompt Engineering, MLOps, LLM Application Development and RAG Pipelines.
Which AI skills should AI Engineer candidates learn next?
MLOps, Prompt Engineering and AI Security are the AI skills employers most often want to add. The most common skill gaps are Prompt Engineering and AI Safety and Red Teaming.
How is the AI Engineer role changing?
The most common direction is AI engineering. Other directions include AI product, AI transformation and data & machine learning.
How much do AI Engineer roles pay in the Netherlands?
Advertised salaries typically range from €4,800 to €6,500 per month, with the median around €5,600, based on 28 postings that quote pay per month.
Find your next AI Engineer role
Browse open AI roles, updated daily.
This guide is built from public job descriptions for AI Engineer roles classified as Core AI or AI-enabled. Skills, automation exposure and career directions are extracted from each job description and compared across the market. Postings are deduplicated, so a job listed on several boards or by several agencies counts once. Salaries are advertised ranges from the Netherlands, taken only from the 28 postings that quote pay. How we collect and deduplicate postings.